{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T21:46:20Z","timestamp":1785879980817,"version":"3.56.0"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100003787","name":"Hebei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["F2024203114"],"award-info":[{"award-number":["F2024203114"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003787","name":"Hebei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["F2025203121"],"award-info":[{"award-number":["F2025203121"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62373319"],"award-info":[{"award-number":["62373319"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62473327"],"award-info":[{"award-number":["62473327"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Communications in Nonlinear Science and Numerical Simulation"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.cnsns.2026.110396","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T23:36:30Z","timestamp":1781739390000},"page":"110396","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P3","title":["Reinforcement learning-based fixed-time human-robot collaboration control without force sensors"],"prefix":"10.1016","volume":"162","author":[{"given":"Yana","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huixin","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junpeng","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.cnsns.2026.110396_bib0001","doi-asserted-by":"crossref","first-page":"1571","DOI":"10.3390\/s21051571","article-title":"Human-robot perception in industrial environments: a survey","volume":"21","author":"Bonci","year":"2021","journal-title":"Sensors"},{"issue":"2","key":"10.1016\/j.cnsns.2026.110396_bib0002","doi-asserted-by":"crossref","first-page":"333","DOI":"10.20517\/ir.2025.17","article-title":"Disturbance observer-based terminal sliding mode control for the training safety improvement in robot-assisted rehabilitation","volume":"5","author":"Zhang","year":"2025","journal-title":"Intell Robot"},{"issue":"2","key":"10.1016\/j.cnsns.2026.110396_bib0003","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1007\/s12369-020-00634-z","article-title":"Assistive robots for the social management of health: a framework for robot design and human\u2013robot interaction research","volume":"13","author":"Chita-Tegmark","year":"2021","journal-title":"Int J Soc Robot"},{"issue":"6","key":"10.1016\/j.cnsns.2026.110396_bib0004","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1007\/s10845-014-0952-1","article-title":"Adaptive neuro fuzzy based hybrid force\/position control for an industrial robot manipulator","volume":"27","author":"Chaudhary","year":"2016","journal-title":"J Intell Manuf"},{"key":"10.1016\/j.cnsns.2026.110396_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.cnsns.2025.109013","article-title":"Ultra-local model-based prescribed-time hybrid force\/position control for 3-DOF series elastic actuator-based manipulator under input and output constraints","author":"Wei","year":"2025","journal-title":"Commun Nonlinear Sci Numer Simul"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0006","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1080\/00207178808906161","article-title":"Robust control of dynamically interacting systems","volume":"48","author":"Colgate","year":"1988","journal-title":"Int J Control"},{"issue":"3","key":"10.1016\/j.cnsns.2026.110396_bib0007","doi-asserted-by":"crossref","first-page":"3351","DOI":"10.1109\/TII.2023.3306574","article-title":"Robust variable impedance control for aerial compliant interaction with stability guarantee","volume":"20","author":"Liang","year":"2023","journal-title":"IEEE Trans Ind Inform"},{"issue":"4","key":"10.1016\/j.cnsns.2026.110396_bib0008","doi-asserted-by":"crossref","first-page":"3138","DOI":"10.1109\/TIE.2019.2912781","article-title":"Force sensorless admittance control with neural learning for robots with actuator saturation","volume":"67","author":"Peng","year":"2019","journal-title":"IEEE Trans Ind Electron"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0009","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1109\/TCST.2016.2523901","article-title":"Adaptive admittance control for human\u2013robot interaction using model reference design and adaptive inverse filtering","volume":"25","author":"Ranatunga","year":"2016","journal-title":"IEEE Trans Control Syst Technol"},{"key":"10.1016\/j.cnsns.2026.110396_bib0010","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.conengprac.2016.11.015","article-title":"Fuzzy logic based adaptive admittance control of a redundantly actuated ankle rehabilitation robot","volume":"59","author":"Ayas","year":"2017","journal-title":"Control Eng Pract"},{"issue":"9","key":"10.1016\/j.cnsns.2026.110396_bib0011","doi-asserted-by":"crossref","first-page":"4551","DOI":"10.1109\/TNNLS.2021.3057958","article-title":"Neural networks enhanced optimal admittance control of robot\u2013environment interaction using reinforcement learning","volume":"33","author":"Peng","year":"2021","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"4","key":"10.1016\/j.cnsns.2026.110396_bib0012","doi-asserted-by":"crossref","first-page":"363","DOI":"10.20517\/ir.2024.22","article-title":"Improved DDPG algorithm-based path planning for unmanned surface vehicles","volume":"4","author":"Hua","year":"2024","journal-title":"Intell Robot"},{"issue":"5","key":"10.1016\/j.cnsns.2026.110396_bib0013","doi-asserted-by":"crossref","first-page":"3282","DOI":"10.1109\/TSMC.2019.2920870","article-title":"Force sensorless admittance control for teleoperation of uncertain robot manipulator using neural networks","volume":"51","author":"Yang","year":"2019","journal-title":"IEEE Trans Syst Man Cybern: Syst"},{"issue":"6","key":"10.1016\/j.cnsns.2026.110396_bib0014","doi-asserted-by":"crossref","first-page":"1292","DOI":"10.1109\/TRO.2017.2723903","article-title":"Robot collisions: a survey on detection, isolation, and identification","volume":"33","author":"Haddadin","year":"2017","journal-title":"IEEE Trans Robot"},{"key":"10.1016\/j.cnsns.2026.110396_bib0015","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1016\/j.isatra.2016.09.015","article-title":"Force estimation and failure detection based on disturbance observer for an ear surgical device","volume":"66","author":"Liang","year":"2017","journal-title":"ISA Trans"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0016","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1109\/TIE.2014.2327009","article-title":"Stability and robustness of disturbance-observer-based motion control systems","volume":"62","author":"Sariyildiz","year":"2014","journal-title":"IEEE Trans Ind Electron"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0017","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1109\/TIE.2007.905976","article-title":"Improving disturbance-rejection performance based on an equivalent-input-disturbance approach","volume":"55","author":"She","year":"2008","journal-title":"IEEE Trans Ind Electron"},{"key":"10.1016\/j.cnsns.2026.110396_bib0018","first-page":"244","article-title":"Disturbance rejection in nonlinear systems based on equivalent-input-disturbance approach","volume":"282","author":"Gao","year":"2016","journal-title":"Appl Math Comput"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0019","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1109\/TMECH.2023.3290564","article-title":"Nonlinearity and disturbance compensation based on improved equivalent-input-disturbance approach","volume":"29","author":"Yin","year":"2023","journal-title":"IEEE\/ASME Trans Mechatron"},{"issue":"5","key":"10.1016\/j.cnsns.2026.110396_bib0020","doi-asserted-by":"crossref","first-page":"5365","DOI":"10.1109\/TIE.2024.3472309","article-title":"Disturbance rejection and performance improvement for control systems using a finite-time equivalent-input-disturbance approach","volume":"72","author":"Wang","year":"2024","journal-title":"IEEE Trans Ind Electron"},{"issue":"12","key":"10.1016\/j.cnsns.2026.110396_bib0021","doi-asserted-by":"crossref","first-page":"2384","DOI":"10.1109\/JAS.2024.124650","article-title":"Disturbance rejection for systems with uncertainties based on fixed-time equivalent-input-disturbance approach","volume":"11","author":"Lu","year":"2024","journal-title":"IEEE\/CAA J Autom Sin"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0022","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cnsns.2010.02.021","article-title":"An adaptive sliding mode control scheme for a class of chaotic systems with mismatched perturbations and input nonlinearities","volume":"16","author":"Xiang","year":"2011","journal-title":"Commun Nonlinear Sci Numer Simul"},{"issue":"12","key":"10.1016\/j.cnsns.2026.110396_bib0023","doi-asserted-by":"crossref","first-page":"3558","DOI":"10.1016\/j.cnsns.2013.04.029","article-title":"Sliding mode control experiments of uncertain dynamical systems with time delay","volume":"18","author":"Qin","year":"2013","journal-title":"Commun Nonlinear Sci Numer Simul"},{"issue":"3","key":"10.1016\/j.cnsns.2026.110396_bib0024","doi-asserted-by":"crossref","first-page":"1264","DOI":"10.1109\/TAC.2019.2926156","article-title":"Finite-time sliding-mode control of markovian jump cyber-physical systems against randomly occurring injection attacks","volume":"65","author":"Cao","year":"2019","journal-title":"IEEE Trans Autom Control"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0025","first-page":"241","article-title":"Adaptive neural network-based fixed-time control for trajectory tracking of robotic systems","volume":"70","author":"Liu","year":"2022","journal-title":"IEEE Trans Circuits Syst II: Express Br"},{"issue":"14","key":"10.1016\/j.cnsns.2026.110396_bib0026","doi-asserted-by":"crossref","first-page":"18229","DOI":"10.1007\/s11071-025-11103-5","article-title":"Adaptive neural network-based fixed-time control for robots with input saturation and prescribed performance","volume":"113","author":"Liu","year":"2025","journal-title":"Nonlinear Dyn"},{"issue":"11","key":"10.1016\/j.cnsns.2026.110396_bib0027","doi-asserted-by":"crossref","first-page":"14823","DOI":"10.1109\/TIE.2024.3366204","article-title":"Adaptive disturbance observer-based fixed-time tracking control for uncertain robotic systems","volume":"71","author":"Liu","year":"2024","journal-title":"IEEE Trans Ind Electron"},{"issue":"4","key":"10.1016\/j.cnsns.2026.110396_bib0028","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1049\/iet-cta.2014.0202","article-title":"Non-singular fixed-time terminal sliding mode control of non-linear systems","volume":"9","author":"Zuo","year":"2015","journal-title":"IET Control Theory Appl"},{"key":"10.1016\/j.cnsns.2026.110396_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.automatica.2024.111716","article-title":"Adaptive practical fixed-time synchronized tracking control of ASV with prescribed performance","volume":"166","author":"Wang","year":"2024","journal-title":"Automatica"},{"issue":"7","key":"10.1016\/j.cnsns.2026.110396_bib0030","doi-asserted-by":"crossref","first-page":"7275","DOI":"10.1109\/TIE.2021.3095820","article-title":"Toward sensorless interaction force estimation for industrial robots using high-order finite-time observers","volume":"69","author":"Han","year":"2021","journal-title":"IEEE Trans Ind Electron"},{"issue":"2","key":"10.1016\/j.cnsns.2026.110396_bib0031","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1109\/TMECH.2024.3436823","article-title":"Force-sensorless active compliance control for environment interactive robotic systems","volume":"30","author":"Liu","year":"2024","journal-title":"IEEE\/ASME Trans Mechatron"},{"issue":"8","key":"10.1016\/j.cnsns.2026.110396_bib0032","doi-asserted-by":"crossref","DOI":"10.1088\/1402-4896\/ad6512","article-title":"Parameters identification and contact interaction control of redundant robot based on dynamic model","volume":"99","author":"Li","year":"2024","journal-title":"Phys Scr"},{"key":"10.1016\/j.cnsns.2026.110396_bib0033","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.automatica.2014.10.082","article-title":"Finite-time and fixed-time stabilization: implicit lyapunov function approach","volume":"51","author":"Polyakov","year":"2015","journal-title":"Automatica"},{"key":"10.1016\/j.cnsns.2026.110396_bib0034","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.automatica.2017.09.007","article-title":"Finite-time and fixed-time observer design: implicit lyapunov function approach","volume":"87","author":"Lopez-Ramirez","year":"2018","journal-title":"Automatica"},{"key":"10.1016\/j.cnsns.2026.110396_bib0035","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1109\/TASE.2024.3359219","article-title":"Application of reinforcement learning-based adaptive PID controller for automatic generation control of multi-area power system","volume":"22","author":"Muduli","year":"2024","journal-title":"IEEE Trans Autom Sci Eng"},{"issue":"4","key":"10.1016\/j.cnsns.2026.110396_bib0036","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1109\/72.298229","article-title":"Radial basis function neural network for approximation and estimation of nonlinear stochastic dynamic systems","volume":"5","author":"Sunil Elanayar","year":"1994","journal-title":"IEEE Trans Neural Netw"},{"issue":"1","key":"10.1016\/j.cnsns.2026.110396_bib0037","first-page":"391","article-title":"A novel non-singular terminal sliding mode trajectory tracking control for robotic manipulators","volume":"68","author":"Zhai","year":"2020","journal-title":"IEEE Trans Circuits Syst II: Express Br"}],"container-title":["Communications in Nonlinear Science and Numerical Simulation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1007570426007501?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1007570426007501?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T21:02:59Z","timestamp":1785877379000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1007570426007501"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":37,"alternative-id":["S1007570426007501"],"URL":"https:\/\/doi.org\/10.1016\/j.cnsns.2026.110396","relation":{},"ISSN":["1007-5704"],"issn-type":[{"value":"1007-5704","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Reinforcement learning-based fixed-time human-robot collaboration control without force sensors","name":"articletitle","label":"Article Title"},{"value":"Communications in Nonlinear Science and Numerical Simulation","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cnsns.2026.110396","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110396"}}